1. Field of the Invention
The present invention relates to an image processing method, and more particularly, to an image compression method for binary digital signals.
2. Description of the Prior Art
Without image compression, the transmission of images requires an unacceptable bandwidth in many applications. As a result, methods of compressing images have been the subject of numerous research publications. Image compression schemes convert an image consisting of a two-dimensional array of pixels into a sequence of bits, which are to be transmitted over a communication link. Each pixel represents the intensity of the image at a particular location therein. The transmission link may be an ordinary telephone line.
Consider an image comprising a gray-scale representation of a photograph at a resolution of 1000×1000 lines. Each pixel typically consists of 8 bits, which are used to encode 256 possible intensity levels at the corresponding point on the photograph. Hence, without compression, transmission of the photograph requires that 8 million bits be sent over the communication link. A typical telephone line is capable of transmitting about 9600 bits per second; hence the picture transmission would require more than 10 minutes. Transmission times of this magnitude are unacceptable.
As a result, image compression systems are needed to reduce the transmission time. It will also be apparent to those skilled in the art that image compression systems may also be advantageously employed in image storage systems to reduce the amount of memory needed to store one or more images.
Image compression involves transforming the image to a form, which can be represented in fewer bits without losing the essential features of the original images. The transformed image is then transmitted over the communication link and the inverse transformation is applied at the receiver to recover the image. The compression of an image typically requires two steps. In the first step, the image is transformed to a new representation in which the correlation between adjacent pixels is reduced. This transformation is usually completely reversible, that is, no information is lost at this stage. The number of bits of data needed to represent the transformed image is at least as large as that needed to represent the original image. The purpose of this transformation is to provide an image representation, which is more ideally suited to known compression methods.
In the second step, referred to as quantization, each pixel in the transformed image is replaced by a value, which is represented in fewer bits, on average, than the original pixel value. In general, the original gray scale is replaced by a new scale, which has coarser steps and hence can be represented in fewer bits. The new gray scale is calculated from the statistical distribution of the pixel values in the transformed image.
The quantized image resulting from the above two steps is often further coded for transmission over the communication link. This coding is completely reversible. Its purpose is to provide a more compact representation of the quantized picture. At the other end of the communication link, the coded image is decoded, the quantization transformation is reversed and the inverse of the first transformation is performed on the resulting image to provide a reconstructed image.
However, the known image compression method usually utilizes a complicated encoding and decoding circuitry to attain the more compact image data for transmission. The coding/decoding process is also complicated. Moreover, the image transformation circuitry is a significant cost factor in image compression apparatuses. The required computational expense clearly depends on the image transformation selected. Hence, an image compression method, which requires less computation than the prior image compression method, would be advantageous.